Consultant, Insights & Analytics

Role & responsibilities

The Data Scientist / Sr. Data Scientist will play a critical role in driving data-driven decision-making for our clients. This role involves leveraging advanced analytics, machine learning, and AI techniques on pharmaceutical industry datasetssuch as sales, claims, and payer datasets from different sources to uncover actionable insights and support strategic business decisions.

A successful candidate should have a strong background in the biopharma and/or healthcare industry, with proven experience in statistical modeling, predictive analytics, and managing complex data science projects. The candidate should be proactive, with a track record of generating impactful insights and delivering data-driven solutions to clients.

The ideal candidate will be adept at building and deploying machine learning models, developing algorithms, and working with large datasets in a Data Lake environment. They should be capable of integrating, harmonizing, and transforming raw data into predictive models and analytical solutions.

Responsibilities:

- Design, develop, and implement machine learning models and algorithms to analyze pharmaceutical datasets (e.g., IQVIA, Symphony, Veeva, Open data) and provide actionable insights.

- Utilize advanced statistical techniques and data science methodologies to drive insights from complex data sources.

- Build and maintain data pipelines and scalable machine learning models on Data Lake architecture, leveraging cloud-based platforms such as AWS (Redshift, S3, SageMaker, etc.).

- Collaborate with cross-functional teams to translate business problems into data science solutions.

- Create and present data visualizations, dashboards, and reports using tools like PowerBI, Tableau, Qlik, QuickSight, and ThoughtSpot to communicate findings and recommendations to clients.

- Conduct exploratory data analysis, data profiling, and feature engineering to prepare datasets for predictive modeling.

- Evaluate model performance, optimize algorithms, and ensure robustness and accuracy in predictions.

- Stay current with the latest advancements in data science, machine learning, and AI, and apply them to ongoing projects.

Qualifications:

- Bachelor's or master's degree in data science, statistics, computer science, engineering, or a related quantitative field with a strong academic record.

- 2-5 years of experience in data science, particularly in the pharmaceutical or healthcare industry, working with key datasets like Sales, Claims, and Payer data.

- Extensive experience in developing and deploying machine learning models, including experience with supervised and unsupervised learning techniques.

- Proficiency in programming languages such as Python and R, with a deep understanding of libraries like TensorFlow, Scikit-learn, and Pandas.

- Strong experience with SQL and cloud-based data processing environments such as AWS (Redshift, Athena, S3), and experience with Jupyter Notebooks/SageMaker.

- Demonstrated ability to build data visualizations and communicate insights through tools like PowerBI, Tableau, Qlik, QuickSight, or similar.

- Strong analytical skills, with experience in hypothesis testing, A/B testing, and statistical analysis.

- Ability to manage multiple projects, prioritize tasks, and meet deadlines in a fast-paced environment.

- Excellent communication and presentation skills, with the ability to explain complex data science concepts to non-technical stakeholders.

- A strong problem-solving mindset, with the ability to adapt and innovate in a dynamic consulting environment.

Equal Employment Opportunity:

Chryselys is proud to be an Equal Employment Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.